# Cell growth prediction model(T-08) ---- ## ==2021/6/30 Meeting 1== --- ### Job Description * Spec pic ![](https://i.imgur.com/5JFYHif.png =x350) --- ### schedule time * WorkFlow chart ![](https://i.imgur.com/y2IAwKw.png =x350) --- ### Step-by-Step Function #### ==Part1優化影像== ![](https://i.imgur.com/1qogVNm.png =x400) --- #### ==Part2建立允收標準== ![](https://i.imgur.com/FVVrQvJ.png =x450) --- ## 開會 * CV訓練分辨 漂浮型+貼附型(Computer vision distinguish cells) * Traning Data (https://github.com/basveeling/pcam) ![](https://i.imgur.com/7BeBOq2.png =x250) * 架構:==MobilenetV2== * [ linear bottleneck + inverted residual--->準確度效能皆可以更加提高](https://medium.com/ai-academy-taiwan/efficient-cnn-%E4%BB%8B%E7%B4%B9-%E4%BA%8C-mobilenetv2-7809721f0bc8) ![](https://i.imgur.com/QIilmaA.png) ![](https://i.imgur.com/qAH47YY.png) --- ## 效果 * 原圖 ![](https://i.imgur.com/cusRPf3.png) * 去背後 ![](https://i.imgur.com/ivpnMEM.png) ---- * [優化參考論文](https://www.ijert.org/research/breast-cancer-cell-detection-using-digital-image-processing-IJERTV1IS9046.pdf) * [SVM K-means](https://www.nature.com/articles/s41598-020-76670-6.pdf) 去粒子 --- [udacity 深度學習課程](https://classroom.udacity.com/courses/ud187/lessons/6d543d5c-6b18-4ecf-9f0f-3fd034acd2cc/concepts/2b6512b8-a5c6-4c2e-a3b7-b63abb27df97) ## 用flask deploy model [Deploy Machine Learning Models using Flask](https://www.youtube.com/watch?v=0nr6TPKlrN0) [falsk 做深度學習開發](https://haosquare.com/tbrain-tomofun-audio-classification/?fbclid=IwAR3GZOtD5nBhGJpm0w0Ld4_A7I5DLzoh0LLz1oR_tDYCR8hlWz2v-JGio5c)